Abstract:
Systems and methods for classifying defects detected on a wafer are provided. One method includes detecting defects on a wafer based on output generated for the wafer by an inspection system. The method also includes determining one or more attributes for at least one of the defects based on portions of a standard reference image corresponding to the at least one of the defects. The method further includes classifying the at least one of the defects based at least in part on the one or more determined attributes.
Abstract:
Methods and systems for detecting defects on a wafer using defect-specific and multi-channel information are provided. One method includes acquiring information for a target on a wafer. The target includes a pattern of interest (POI) formed on the wafer and a known defect of interest (DOI) occurring proximate to or in the POI. The method also includes detecting the known DOI in target candidates by identifying potential DOI locations based on images of the target candidates acquired by a first channel of an inspection system and applying one or more detection parameters to images of the potential DOI locations acquired by a second channel of the inspection system. Therefore, the image(s) used for locating potential DOI locations and the image(s) used for detecting defects can be different.
Abstract:
Methods and systems for transforming positions of defects detected on a wafer are provided. One method includes aligning output of an inspection subsystem for a first frame in a first swath in a first die in a first instance of a multi-die reticle printed on the wafer to the output for corresponding frames, swaths, and dies in other reticle instances printed on the wafer. The method also includes determining different swath coordinate offsets for each of the frames, respectively, in the other reticle instances based on the swath coordinates of the output for the frames and the corresponding frames aligned thereto and applying one of the different swath coordinate offsets to the swath coordinates reported for the defects based on the other reticle instances in which they are detected thereby transforming the swath coordinates for the defects from swath coordinates in the other reticle instances to the first reticle instance.
Abstract:
A method may include, but is not limited to, receiving a plurality of reference images of a wafer. The method may include, but is not limited to, receiving the plurality of test images of the wafer. The method may include, but is not limited to, aligning the plurality of reference images and the plurality of test images via a coarse alignment process. The method may include, but is not limited to, aligning the plurality of reference images and the plurality of test images via a fine alignment process after alignment via the coarse alignment process. The fine alignment process may include measuring individual offsets and correcting individual offset data between at least one of the plurality of reference images and the plurality of test images.
Abstract:
Methods and systems for detecting defects on a wafer using defect-specific and multi-channel information are provided. One method includes acquiring information for a target on a wafer. The target includes a pattern of interest (POI) formed on the wafer and a known defect of interest (DOI) occurring proximate to or in the POI. The method also includes detecting the known DOI in target candidates by identifying potential DOI locations based on images of the target candidates acquired by a first channel of an inspection system and applying one or more detection parameters to images of the potential DOI locations acquired by a second channel of the inspection system. Therefore, the image(s) used for locating potential DOI locations and the image(s) used for detecting defects can be different.
Abstract:
Methods and systems for detecting defects on a wafer using adaptive local thresholding and color filtering are provided. One method includes determining local statistics of pixels in output for a wafer generated using an inspection system, determining which of the pixels are outliers based on the local statistics, and comparing the outliers to the pixels surrounding the outliers to identify the outliers that do not belong to a cluster of outliers as defect candidates, The method also includes determining a value for a difference in color between the pixels of the defect candidates and the pixels surrounding the defect candidates. The method further includes identifying the defect candidates that have a value for the difference in color greater than or equal to a predetermined value as nuisance defects and the defect candidates that have a value for the difference in color less than the predetermined value as real defects,
Abstract:
A method includes identifying a first set of a first care area with a first sensitivity threshold, the first care area associated with a first design of interest within a block of repeating cells in design data; identifying an additional set of an additional care area with an additional sensitivity threshold, the additional care area associated with an additional design of interest within the block of repeating cells in design data; identifying one or more defects within the first set of the first care areas in one or more images of a selected region of a sample based on the first sensitivity threshold; and identifying one or more defects within the additional set of the additional care areas in the one or more images of the selected region of the sample based on the additional sensitivity threshold.
Abstract:
Methods and systems for detecting defects on a wafer using defect-specific and multi-channel information are provided. One method includes acquiring information for a target on a wafer. The target includes a pattern of interest (POI) formed on the wafer and a known defect of interest (DOI) occurring proximate to or in the POI. The method also includes detecting the known DOI in target candidates by identifying potential DOI locations based on images of the target candidates acquired by a first channel of an inspection system and applying one or more detection parameters to images of the potential DOI locations acquired by a second channel of the inspection system. Therefore, the image(s) used for locating potential DOI locations and the image(s) used for detecting defects can be different.
Abstract:
Systems and methods for discovering defects on a wafer are provided. One method includes detecting defects on a wafer by applying a threshold to output generated by a detector in a first scan of the wafer and determining values for features of the detected defects. The method also includes automatically ranking the features, identifying feature cut-lines to group the defect into bins, and, for each of the bins, determining one or more parameters that if applied to the values for the features of the defects in each of the bins will result in a predetermined number of the defects in each of the bins. The method also includes applying the one or more determined parameters to the output generated by the detector in a second scan of the wafer to generate a defect population that has a predetermined defect count and is diversified in the values for the features.
Abstract:
Systems and methods for detecting defects on a wafer are provided. One method includes generating test image(s) for at least a portion of an array region in die(s) on a wafer from frame image(s) generated by scanning the wafer with an inspection system. The method also includes generating a reference image for cell(s) in the array region from frame images generated by the scanning of the wafer. In addition, the method includes determining difference image(s) for at least one cell in the at least the portion of the array region in the die(s) by subtracting the reference image from portion(s) of the test image(s) corresponding to the at least one cell. The method further includes detecting defects on the wafer in the at least one cell based on the difference image(s).